Metric details with threshold from accuracy metric
score
threshold
logloss
0.436436
nan
auc
0.870434
nan
f1
0.825652
0.518668
accuracy
0.79896
0.518668
precision
0.791353
0.518668
recall
0.863059
0.518668
mcc
0.592415
0.518668
Confusion matrix (at threshold=0.518668)
Predicted as long
Predicted as short
Labeled as long
1428
555
Labeled as short
334
2105
Learning curves
Decision Tree
Tree #1
Rules
if (Total Costs <= 7840.645) and (CCS Diagnosis Code <= 454.5) and (Total Costs <= 4864.71) then class: short (proba: 95.04%) | based on 3,269 samples
if (Total Costs <= 7840.645) and (CCS Diagnosis Code <= 454.5) and (Total Costs > 4864.71) then class: short (proba: 74.99%) | based on 2,363 samples
if (Total Costs > 7840.645) and (APR Severity of Illness Code > 2.5) and (Total Costs > 11670.13) then class: long (proba: 92.99%) | based on 2,211 samples
if (Total Costs > 7840.645) and (APR Severity of Illness Code <= 2.5) and (APR Medical Surgical Description <= 1.5) then class: long (proba: 71.26%) | based on 2,150 samples
if (Total Costs > 7840.645) and (APR Severity of Illness Code <= 2.5) and (APR Medical Surgical Description > 1.5) then class: short (proba: 57.91%) | based on 2,036 samples
if (Total Costs > 7840.645) and (APR Severity of Illness Code > 2.5) and (Total Costs <= 11670.13) then class: long (proba: 69.95%) | based on 599 samples
if (Total Costs <= 7840.645) and (CCS Diagnosis Code > 454.5) and (Total Costs > 3798.055) then class: long (proba: 76.8%) | based on 362 samples
if (Total Costs <= 7840.645) and (CCS Diagnosis Code > 454.5) and (Total Costs <= 3798.055) then class: short (proba: 80.73%) | based on 275 samples